Search results for: robust scheduling

Authors: Ram Mohan, Richard Haney, Ajit Kelkar

Abstract:

Current developments in computing have shown the advantage of using one or more Graphic Processing Units (GPU) to boost the performance of many computationally intensive applications but there are still limits to these GPU-enhanced systems. The major factors that contribute to the limitations of GPU(s) for High Performance Computing (HPC) can be categorized as hardware and software oriented in nature. Understanding how these factors affect performance is essential to develop efficient and robust applications codes that employ one or more GPU devices as powerful co-processors for HPC computational modeling. This research and technical presentation will focus on the analysis and understanding of the intrinsic interrelationship of both hardware and software categories on computational performance for single and multiple GPU-enhanced systems using a computationally intensive application that is representative of a large portion of challenges confronting modern HPC. The representative application uses unstructured finite element computations for transient composite resin infusion process flow modeling as the computational core, characteristics and results of which reflect many other HPC applications via the sparse matrix system used for the solution of linear system of equations. This work describes these various software and hardware factors and how they interact to affect performance of computationally intensive applications enabling more efficient development and porting of High Performance Computing applications that includes current, legacy, and future large scale computational modeling applications in various engineering and scientific disciplines.

Keywords: graphical processing unit, software development and engineering, performance analysis, system architecture and software performance

Procedia PDF Downloads 343

Authors: Omaima N. Ahmad AL-Allaf

Abstract:

Over communication networks, images can be easily copied and distributed in an illegal way. The copyright protection for authors and owners is necessary. Therefore, the digital watermarking techniques play an important role as a valid solution for authority problems. Digital image watermarking techniques are used to hide watermarks into images to achieve copyright protection and prevent its illegal copy. Watermarks need to be robust to attacks and maintain data quality. Therefore, we discussed in this paper two approaches for image watermarking, first is based on Particle Swarm Optimization (PSO) and the second approach is based on Genetic Algorithm (GA). Discrete wavelet transformation (DWT) is used with the two approaches separately for embedding process to cover image transformation. Each of PSO and GA is based on co-relation coefficient to detect the high energy coefficient watermark bit in the original image and then hide the watermark in original image. Many experiments were conducted for the two approaches with different values of PSO and GA parameters. From experiments, PSO approach got better results with PSNR equal 53, MSE equal 0.0039. Whereas GA approach got PSNR equal 50.5 and MSE equal 0.0048 when using population size equal to 100, number of iterations equal to 150 and 3×3 block. According to the results, we can note that small block size can affect the quality of image watermarking based PSO/GA because small block size can increase the search area of the watermarking image. Better PSO results were obtained when using swarm size equal to 100.

Keywords: image watermarking, genetic algorithm, particle swarm optimization, discrete wavelet transform

Procedia PDF Downloads 195

Authors: Ben J. Lippe

Abstract:

Consult Liaison Psychology services are overgrowing, given the robust empirical support of the utility of this service in hospital settings. These psychological services, including clinical assessment, applied psychotherapy, and consultation with other healthcare providers, have been shown to improve health outcomes for patients and bolster important areas of administrative interest such as decreased length of patient admission. However, there is little descriptive literature outlining the process and mechanisms of building or developing a Consult Liaison Psychology service. The main findings of this current conceptual work are intended to be clear in nature to elucidate the essential methods involved in developing consult liaison psychology programs, including thorough reviews of relevant behavioral health literature and inclusion of experiential outcomes. The diverse range of hospital settings and healthcare systems makes a “blueprint” method of program development challenging to define, yet important structural frameworks presented here based on the relevant literature and applied practice can help lay critical groundwork for program development in this growing area of psychological service. This conceptual approach addresses the prominent processes, as well as common programmatic and clinical pitfalls, involved in the event of a Consult Liaison Psychology service. This paper, including a systematic review of relevant literature, is intended to serve as a key program development reference for the development of Consult Liaison Psychology services, other related behavioral health programs, and to help inform further research efforts.

Keywords: behavioral health, consult liaison, health psychology, psychology program development

Procedia PDF Downloads 126

Authors: Layla El Gaini, Majdouline Belaqziz, Meriem Outaki, Mariam Minhaj

Abstract:

In this study, it introduce and validate a high-performance liquid chromatography method with diode-array detection (HPLC-DAD) specifically designed for the accurate quantification of caffeic acid in phenolic extracts obtained from olive mill wastewater. The separation process of caffeic acid was effectively achieved through the use of an Acclaim Polar Advantage column (5µm, 250x4.6mm). A meticulous multi-step gradient mobile phase was employed, comprising water acidified with phosphoric acid (pH 2.3) and acetonitrile, to ensure optimal separation. The diode-array detection was adeptly conducted within the UV–VIS spectrum, spanning a range of 200–800 nm, which facilitated precise analytical results. The method underwent comprehensive validation, addressing several essential analytical parameters, including specificity, repeatability, linearity, as well as the limits of detection and quantification, alongside measurement uncertainty. The generated linear standard curves displayed high correlation coefficients, underscoring the method's efficacy and consistency. This validated approach is not only robust but also demonstrates exceptional reliability for the focused analysis of caffeic acid within the intricate matrices of wastewater, thus offering significant potential for applications in environmental and analytical chemistry.

Keywords: high-performance liquid chromatography (HPLC-DAD), caffeic acid analysis, olive mill wastewater phenolics, analytical method validation

Procedia PDF Downloads 41

Authors: Leigh Ann Wilson, Melanie Borrego

Abstract:

The purpose of institutional learning outcomes (ILOs) is to assess what students across the university know and what they do not. The issue is gathering this information in a systematic and usable way. This presentation will explain how one institution has engineered this process for both student success and maximum faculty curriculum and course design input. At Brandman University, there are three levels of learning outcomes: course, program, and institutional. Institutional Learning Outcomes (ILOs) are mapped to specific courses. Faculty course developers write the signature assignments (SAs) in alignment with the Institutional Learning Outcomes for each course. These SAs use a specific rubric that is applied consistently by every section and every instructor. Each year, the 12-member General Education Team (GET), as a part of their work, conducts the calibration and assessment of the university-wide SAs and the related rubrics for one or two of the five ILOs. GET members, who are senior faculty and administrators who represent each of the university's schools, lead the calibration meetings. Specifically, calibration is a process designed to ensure the accuracy and reliability of evaluating signature assignments by working with peer faculty to interpret rubrics and compare scoring. These calibration meetings include the full time and adjunct faculty members who teach the course to ensure consensus on the application of the rubric. Each calibration session is chaired by a GET representative as well as the course custodian/contact where the ILO signature assignment resides. The overall calibration process GET follows includes multiple steps, such as: contacting and inviting relevant faculty members to participate; organizing and hosting calibration sessions; and reviewing and discussing at least 10 samples of student work from class sections during the previous academic year, for each applicable signature assignment. Conversely, the commitment for calibration teams consist of attending two virtual meetings lasting up to three hours in duration. The first meeting focuses on interpreting the rubric, and the second meeting involves comparing scores for sample work and sharing feedback about the rubric and assignment. Next, participants are expected to follow all directions provided and participate actively, and respond to scheduling requests and other emails within 72 hours. The virtual meetings are recorded for future institutional use. Adjunct faculty are paid a small stipend after participating in both calibration meetings. Full time faculty can use this work on their annual faculty report for "internal service" credit.

Keywords: assessment, assurance of learning, course design, institutional learning outcomes, rubrics, signature assignments

Procedia PDF Downloads 258

Authors: Seyed Hamed Hashemi Sohi, Gerald Jo Denoga

Abstract:

Machining or metal cutting is one of the most widely used production processes in industry. The quality of the process and the resulting machined product depends on parameters like tool geometry, material, and cutting conditions. However, the relationships of these parameters to the cutting process are often based mostly on empirical knowledge. In this study, computer modeling and simulation using LS-DYNA software and a Smoothed Particle Hydrodynamic (SPH) methodology, was performed on the orthogonal metal cutting process to analyze three-dimensional deformation of AISI 1045 medium carbon steel during machining. The simulation was performed using the following constitutive models: the Power Law model, the Johnson-Cook model, and the Zerilli-Armstrong models (Z-A). The outcomes were compared against the simulated results obtained by Cenk Kiliçaslan using the Finite Element Method (FEM) and the empirical results of Jaspers and Filice. The analysis shows that the SPH method combined with the Zerilli-Armstrong constitutive model is a viable alternative to simulating the metal cutting process. The tangential force was overestimated by 7%, and the normal force was underestimated by 16% when compared with empirical values. The simulation values for flow stress versus strain at various temperatures were also validated against empirical values. The SPH method using the Z-A model has also proven to be robust against issues of time-scaling. Experimental work was also done to investigate the effects of friction, rake angle and tool tip radius on the simulation.

Keywords: metal cutting, smoothed particle hydrodynamics, constitutive models, experimental, cutting forces analyses

Procedia PDF Downloads 238

Authors: Parthiban Srinivasan

Abstract:

With recent advances in computational power and access to enough data in biosciences, artificial intelligence methods are increasingly being used in drug discovery research. These methods are essentially a series of advanced statistics based exercises that review the past to indicate the likely future. Our goal is to develop a model that accurately predicts biological activity and toxicity parameters for novel compounds. We have compiled a robust library of over 150,000 chemical compounds with different pharmacological properties from literature and public domain databases. The compounds are stored in simplified molecular-input line-entry system (SMILES), a commonly used text encoding for organic molecules. We utilize an automated process to generate an array of numerical descriptors (features) for each molecule. Redundant and irrelevant descriptors are eliminated iteratively. Our prediction engine is based on a portfolio of machine learning algorithms. We found Random Forest algorithm to be a better choice for this analysis. We captured non-linear relationship in the data and formed a prediction model with reasonable accuracy by averaging across a large number of randomized decision trees. Our next step is to apply deep neural network (DNN) algorithm to predict the biological activity and toxicity properties. We expect the DNN algorithm to give better results and improve the accuracy of the prediction. This presentation will review all these prominent machine learning and deep learning methods, our implementation protocols and discuss these techniques for their usefulness in biomedical and health informatics.

Keywords: deep learning, drug discovery, health informatics, machine learning, toxicity prediction

Procedia PDF Downloads 334

Authors: Rodrigo T. Sepulveda-Hirose, Ana B. Carrera-Aguilar, Magnolia G. Martinez-Rivera, Pablo de J. Angeles-Salto, Carlos Herrera-Ventosa

Abstract:

In order to diminish health risks, it is of major importance to monitor air quality. However, this process is accompanied by the high costs of physical and human resources. In this context, this research is carried out with the main objective of developing a predictive model for concentrations of inhalable particles (PM10-2.5) using remote sensing. To develop the model, satellite images, mainly from Landsat 8, of the Mexico City’s Metropolitan Area were used. Using historical PM10 and PM2.5 measurements of the RAMA (Automatic Environmental Monitoring Network of Mexico City) and through the processing of the available satellite images, a preliminary model was generated in which it was possible to observe critical opportunity areas that will allow the generation of a robust model. Through the preliminary model applied to the scenes of Mexico City, three areas were identified that cause great interest due to the presumed high concentration of PM; the zones are those that present high plant density, bodies of water and soil without constructions or vegetation. To date, work continues on this line to improve the preliminary model that has been proposed. In addition, a brief analysis was made of six models, presented in articles developed in different parts of the world, this in order to visualize the optimal bands for the generation of a suitable model for Mexico City. It was found that infrared bands have helped to model in other cities, but the effectiveness that these bands could provide for the geographic and climatic conditions of Mexico City is still being evaluated.

Keywords: air quality, modeling pollution, particulate matter, remote sensing

Procedia PDF Downloads 132

Authors: Abdul Waris Jalili, Yanqing Wang, Som Suor

Abstract:

This research paper explores the relationship between entrepreneurship education and students' entrepreneurial intentions. It aims to determine if entrepreneurship education reliably predicts students' intention to become entrepreneurs and how and when this relationship occurs. This study aims to investigate the predictive relationship between entrepreneurship education and student entrepreneurial intentions. The goal is to understand the factors that influence this relationship and to identify any mediating or moderating factors. A thorough and systematic search and review of empirical articles published between 2013 and 2023 were conducted. Three databases, Google Scholar, Science Direct, and PubMed, were explored to gather relevant studies. Criteria such as reporting empirical results, publication in English, and addressing the research questions were used to select 35 papers for analysis. The collective findings of the reviewed studies suggest a generally positive relationship between entrepreneurship education and student entrepreneurial intentions. However, recent findings indicate that this relationship may be more complex than previously thought. Mediators and moderators have been identified, highlighting instances where entrepreneurship education indirectly influences student entrepreneurial intentions. The review also emphasizes the need for more robust research designs to establish causality in this field. This research adds to the existing literature by providing a comprehensive review of the relationship between entrepreneurship education and student entrepreneurial intentions. It highlights the complexity of this relationship and the importance of considering mediators and moderators. The study also calls for future research to explore different facets of entrepreneurship education independently and examine complex relationships more comprehensively.

Keywords: entrepreneurship, entrepreneurship education, entrepreneurial intention, entrepreneurial self-efficacy

Procedia PDF Downloads 31

Authors: A. Cerrato Casado, C. Guigou, P. Jean

Abstract:

In this investigation, the particle swarm optimization (PSO) algorithm is used to perform the inversion of the dispersion curves in the spectral analysis of surface waves (SASW) method. This inverse problem usually presents complicated solution spaces with many local minima that make difficult the convergence to the correct solution. PSO is a metaheuristic method that was originally designed to simulate social behavior but has demonstrated powerful capabilities to solve inverse problems with complex space solution and a high number of variables. The dispersion curve of the synthetic soils is constructed by the vertical flexibility coefficient method, which is especially convenient for soils where the stiffness does not increase gradually with depth. The reason is that these types of soil profiles are not normally dispersive since the dominant mode of Rayleigh waves is usually not coincident with the fundamental mode. Multiple synthetic soil profiles have been tested to show the characteristics of the convergence process and assess the accuracy of the final soil profile. In addition, the inversion procedure is applied to multiple real soils and the final profile compared with the available information. The combination of the vertical flexibility coefficient method to obtain the dispersion curve and the PSO algorithm to carry out the inversion process proves to be a robust procedure that is able to provide good solutions for complex soil profiles even with scarce prior information.

Keywords: dispersion, inverse problem, particle swarm optimization, SASW, soil profile

Procedia PDF Downloads 157

Authors: Hao-Wei Fu, Chung-Feng Kao

Abstract:

In the era of rapid technological advancement, information technology (IT) has become integral to modern life, exerting significant influence across diverse sectors and serving as a catalyst for development in various industries. Within agriculture, the integration of IT offers substantial benefits, notably enhancing operational efficiency. Real-time monitoring systems, for instance, have been widely embraced in agriculture, effectively improving crop management practices. This study specifically addresses the management of rice panicle fertilizer, presenting the development of a web application tailored to handle data associated with rice panicle fertilizer management. Leveraging the normalized difference red edge index, this application optimizes the quantity of rice panicle fertilizer used, providing recommendations to agricultural stakeholders and service providers in the agricultural information sector. The overarching objective is to minimize costs while maximizing yields. Furthermore, a robust database system has been established to store and manage relevant data for future reference in rice cultivation management. Additionally, the study utilizes the Representational State Transfer software architectural style to construct an application programming interface (API), facilitating data creation, retrieval, updating, and deletion for users via the HyperText Transfer Protocol methods. Future plans involve integrating this API with third-party services to incorporate it into larger frameworks, thus catering to the diverse requirements of various third-party services.

Keywords: application programming interface, HyperText Transfer Protocol, nitrogen fertilizer intelligent management, web-based application

Procedia PDF Downloads 34

Authors: Micheale Yifter Weldemichael, Hailay Mehari Gebremedhn, Teklehaimanot Hailesslasie

Abstract:

The advancement of target-specific genome editing tools, including clustered regularly interspaced short palindromic repeats (CRISPR)/CRISPR-associated protein9 (Cas9), mega-nucleases, base editing (BE), prime editing (PE), transcription activator-like endonucleases (TALENs), and zinc-finger nucleases (ZFNs), have paved the way for a modern era of gene editing. CRISPR/Cas9, as a versatile, simple, cost-effective and robust system for genome editing, has dominated the genome manipulation field over the last few years. The application of CRISPR/Cas9 in sorghum improvement is particularly vital in the context of ecological, environmental and agricultural challenges, as well as global climate change. In this context, gene editing using CRISPR/Cas9 can improve nutritional value, yield, resistance to pests and disease and tolerance to different abiotic stress. Moreover, CRISPR/Cas9 can potentially perform complex editing to reshape already available elite varieties and new genetic variations. However, existing research is targeted at improving even further the effectiveness of the CRISPR/Cas9 genome editing techniques to fruitfully edit endogenous sorghum genes. These findings suggest that genome editing is a feasible and successful venture in sorghum. Newer improvements and developments of CRISPR/Cas9 techniques have further qualified researchers to modify extra genes in sorghum with improved efficiency. The fruitful application and development of CRISPR techniques for genome editing in sorghum will not only help in gene discovery, creating new, improved traits in sorghum regulating gene expression sorghum functional genomics, but also in making site-specific integration events.

Keywords: CRISPR/Cas9, genome editing, quality, sorghum, stress, yield

Procedia PDF Downloads 37

Authors: Shibinu S, Mohamed Haseeb N

Abstract:

In times of crisis, the diaspora's role and the help it offers are seen to be vital in determining how many countries, particularly low- and middle-income nations that significantly rely on remittances, recover. Twenty-one lakh twenty thousand Keralites have emigrated abroad, with 81.2 percent of these outflows occurring in the Gulf Cooperative Council (GCC). Most of them are semi-skilled or low-skilled laborers employed in GCC nations. Additionally, a sizeable portion of migrants are employed in industrialized nations like the UK and the US. These nations have seen the development of a highly robust Indian Diaspora. India's development is largely dependent on the generosity of its diaspora, and the nation has benefited greatly from the substantial contributions made by several emigrant generations. Its strength was noticeable during the COVID-19 and Kerala floods. Millions of people were displaced, millions of properties were damaged, and many people died as a result of the 2018 Kerala floods. The Malayalee diaspora played a crucial role in the reconstruction of Kerala by providing support for the rescue efforts underway on the ground through their extensive worldwide network. During COVID-19, an analogous outreach was also noted, in which the diaspora assisted stranded migrants across the globe. Together with the work the diaspora has done for the state's development and recovery, there has also been a recent outpouring of assistance during the COVID-19 pandemic. The study focuses on the subtleties of diaspora philanthropic scholarship and how Kerala was able to recover from the COVID-19 pandemic and floods thanks to it. Semi-structured in-depth interviews with migrants, migrant organizations, and beneficiaries from the diaspora through snowball sampling to better understand the role that diaspora philanthropy plays in times of crisis.

Keywords: crises, diaspora, remittances, COVID-19, flood, economic development of Kerala

Procedia PDF Downloads 16

Authors: Meng Su

Abstract:

High-dimensional data analysis often presents challenges in capturing the complex, nonlinear relationships and manifold structures inherent to the data. This article presents a novel approach that leverages the strengths of two powerful techniques, Diffusion Maps and Diffusion Probabilistic Models (DPMs), to address these challenges. By integrating the dimensionality reduction capability of Diffusion Maps with the data modeling ability of DPMs, the proposed method aims to provide a comprehensive solution for analyzing and generating high-dimensional data. The Diffusion Map technique preserves the nonlinear relationships and manifold structure of the data by mapping it to a lower-dimensional space using the eigenvectors of the graph Laplacian matrix. Meanwhile, DPMs capture the dependencies within the data, enabling effective modeling and generation of new data points in the low-dimensional space. The generated data points can then be mapped back to the original high-dimensional space, ensuring consistency with the underlying manifold structure. Through a detailed example implementation, the article demonstrates the potential of the proposed hybrid approach to achieve more accurate and effective modeling and generation of complex, high-dimensional data. Furthermore, it discusses possible applications in various domains, such as image synthesis, time-series forecasting, and anomaly detection, and outlines future research directions for enhancing the scalability, performance, and integration with other machine learning techniques. By combining the strengths of Diffusion Maps and DPMs, this work paves the way for more advanced and robust data analysis methods.

Keywords: diffusion maps, diffusion probabilistic models (DPMs), manifold learning, high-dimensional data analysis

Procedia PDF Downloads 74

Authors: Vedansh Gupta, Allyson Lutz, Ameen Razavi, Fatemeh Shirazi

Abstract:

The agriculture industry is especially vulnerable to forecasted water shortages. In the fresh and fresh-cut produce sector, conventional flume-based washing with recirculation exhibits high water demand. This leads to a large water footprint and possible cross-contamination of pathogens. These can be alleviated through advanced water reuse processes, such as membrane technologies including reverse osmosis (RO). Water reuse technologies effectively remove dissolved constituents but can easily foul without pre-treatment. Biological treatment is effective for the removal of organic compounds responsible for fouling, but not at the low temperatures encountered at most produce processing facilities. This study showed that the Microvi MicroNiche Engineering (MNE) technology effectively removes organic compounds (> 80%) at low temperatures (6-8 °C) from wash water. The MNE technology uses synthetic microorganism-material composites with negligible solids production, making it advantageously situated as an effective bio-pretreatment for RO. A preliminary technoeconomic analysis showed 60-80% savings in operation and maintenance costs (OPEX) when using the Microvi MNE technology for organics removal. This study and the accompanying economic analysis indicated that the proposed technology process will substantially reduce the cost barrier for adopting water reuse practices, thereby contributing to increased food safety and furthering sustainable water reuse processes across the agricultural industry.

Keywords: biological pre-treatment, innovative technology, vegetable processing, water reuse, agriculture, reverse osmosis, MNE biocatalysts

Procedia PDF Downloads 107

Authors: Armin Khaghani Boroujeni, Leila Dehghani, Parham Talebi Boroujeni, Sahar Rostamian, Ali Asilian

Abstract:

Background: Hair loss is a common complaint observed in both genders. Androgenetic alopecia is known pattern for hair loss. To assess new regenerative strategies (PRP, A-SC-BT, conditioned media, exosome-based treatments) compared to conventional therapies for hair loss or hair regeneration, an updated review was undertaken. To address this issue, we carried out this systematic review to comprehensively evaluate the efficacy of cell-based therapies on hair loss. Methods: The available online databases, including ISI Web of Science, Scopus, and PubMed, were searched systematically up to February 2022. The quality assessment of included studies was done using the Cochrane Collaboration's tool. Results: As a result, a total of 90 studies involving 2345 participants were included in the present study. The enrolled studies were conducted between 2010 and 2022. The subjects’ mean age ranged from 19 to 55.11 years old. Approaches using platelet rich plasma (PRP) provide a beneficial impact on hair regrowth. However, other cell-based therapies, including stem cell transplant, stem cell-derived conditioned medium, and stem cell-derived exosomes, revealed conflicting evidence. Conclusion: However, cell-based therapies for hair loss are still in their infancy, and more robust clinical studies are needed to better evaluate their mechanisms of action, efficacy, safety, benefits, and limitations. In this review, we provide the resources to the latest clinical studies and a more detailed description of the latest clinical studies concerning cell-based therapies in hair loss.

Keywords: cell-based therapy, exosome, hair restoration, systematic review

Procedia PDF Downloads 54

Authors: Salma Baig, Bakrudeen Ali Ahmad, Ainnul Hamidah Syahadah Azizan, Hapipah Mohd Ali, Elham Rouhollahi, Mahmood Ameen Abdulla

Abstract:

Free radical damage induced by reactive oxygen species (ROS) contributes to etiology of many chronic diseases, cancer being one of them. Recent studies have been successful in ROS targeted therapies via antioxidants using mouse models in cancer therapeutics. The present study was designed to scrutinize anticancer activity, antioxidant activity of 5 different extracts of Thymus serpyllum in MDA-MB-231, MCF-7, HepG2, HCT-116, PC3, and A549. Identification of the phytochemicals present in the most active extract of Thymus serpyllum was conducted using gas chromatography coupled with mass spectrophotometry and antioxidant activity was measured by using DPPH radical scavenging and FRAP assay. Anticancer impact of the extract in terms of IC50 was evaluated using MTT cell viability assay. Results revealed that the hexane extract showed the best anticancer activity in HepG2 (Liver Carcinoma Cell Line) with an IC50 value of 23 ± 0.14 µg/ml followed by 25 µg/ml in HCT-116 (Colon Cancer Cell Line), 30 µm/ml in MCF-7 (Breast Cancer Cell Line), 35 µg/ml in MDA-MB-231 (Breast Cancer Cell Line), 57 µg/ml in PC3 (Prostate Cancer Cell Line) and 60 µg/ml in A549 (Lung Carcinoma Cell Line). GC-MS profile of the hexane extract showed the presence of 31 compounds with carvacrol, thymol and thymoquione being the major compounds. Phenolics such as Vitamin E, terpinen-4-ol, borneol and phytol were also identified. Hence, here we present the first report on cytotoxicity of hexane extract of Thymus serpyllum extract in HepG2 cell line with a robust anticancer activity with an IC50 of 23 ± 0.14 µg/ml.

Keywords: Thymus serpyllum L., hexane extract, GC-MS profile, antioxidant activity, anticancer activity, HepG2 cell line

Procedia PDF Downloads 478

Authors: Jalal Maqbool, Gyu Myoung Lee

Abstract:

Using smart devices for context aware mobile learning is becoming increasingly popular. This has led to mobile learning technology becoming an indispensable part of today’s learning environment and platforms. However, some fundamental issues remain - namely, mobile learning still lacks the ability to truly understand human reaction and user behaviour. This is due to the fact that current mobile learning systems are passive and not aware of learners’ changing contextual situations. They rely on static information about mobile learners. In addition, current mobile learning platforms lack the capability to incorporate dynamic contextual situations into learners’ preferences. Thus, this thesis aims to address these issues highlighted by designing a context aware framework which is able to sense learner’s contextual situations, handle data dynamically, and which can use contextual information to suggest bespoke learning content according to a learner’s preferences. This is to be underpinned by a robust recommendation system, which has the capability to perform these functions, thus providing learners with a truly context-aware mobile learning experience, delivering learning contents using smart devices and adapting to learning preferences as and when it is required. In addition, part of designing an algorithm for the recommendation engine has to be based on learner and application needs, personal characteristics and circumstances, as well as being able to comprehend human cognitive processes which would enable the technology to interact effectively and deliver mobile learning content which is relevant, according to the learner’s contextual situations. The concept of this proposed project is to provide a new method of smart learning, based on a capable recommendation engine for providing an intuitive mobile learning model based on learner actions.

Keywords: aware, context, learning, mobile

Procedia PDF Downloads 222

Authors: Farzan Farhangian, Behnam Shakibafar, Bobda Cedric, Rene Jr. Landry

Abstract:

Among the air navigation technologies, many of them are capable of increasing aviation sustainability as well as accuracy improvement in Alternative Positioning, Navigation, and Timing (APNT), especially avionics Distance Measuring Equipment (DME), Very high-frequency Omni-directional Range (VOR), etc. The integration of these air navigation solutions could make a robust and efficient accuracy in air mobility, air traffic management and autonomous operations. Designing a proper RF front-end, power amplifier and software-defined transponder could pave the way for reaching an optimized avionics navigation solution. In this article, the possibility of reaching an optimum front-end to be used with single low-cost Software-Defined Radio (SDR) has been investigated in order to reach a software-defined DME architecture. Our software-defined approach uses the firmware possibilities to design a real-time software architecture compatible with a Multi Input Multi Output (MIMO) BladeRF to estimate an accurate time delay between a Transmission (Tx) and the reception (Rx) channels using the synchronous scheduled communication. We could design a novel power amplifier for the transmission channel of the DME to pass the minimum transmission power. This article also investigates designing proper pair pulses based on the DO-178B avionics standard. Various guidelines have been tested, and the possibility of passing the certification process for each standard term has been analyzed. Finally, the performance of the DME was tested in the laboratory environment using an IFR6000, which showed that the proposed architecture reached an accuracy of less than 0.23 Nautical mile (Nmi) with 98% probability.

Keywords: avionics, DME, software defined radio, navigation

Procedia PDF Downloads 53

Authors: Marie Madeleine Sarzi Inacio, Ligiane Carolina Leite Dauzacker, Rodrigo Henriques Lopes Da Silva

Abstract:

The climate changes resulting from human activity have increased interest in more sustainable production practices to reduce and offset pollutant emissions. Brazil, with its vast areas capable of carbon absorption, holds a significant advantage in this context. However, to optimize the country's sustainable potential, it is important to establish a robust carbon market with clear rules for the eligibility and validation of projects aimed at reducing and offsetting Greenhouse Gas (GHG) emissions. In this study, our objective is to conduct a feasibility analysis through a case study to evaluate the implementation of an urban forest credits standard in Brazil, using the Urban Forest Credits (UFC) model implemented in the United States as a reference. Thus, the city of Ribeirão Preto, located in Brazil, was selected to assess the availability of green areas. With the CO2 emissions value from the metalworking industry, it was possible to analyze information in the case study, considering the activity. The QGIS software was used to map potential urban forest areas, which can connect to various types of geospatial databases. Although the chosen municipality has little vegetative coverage, the mapping identified at least eight areas that fit the standard definitions within the delimited urban perimeter. The outlook was positive, and the implementation of projects like Urban Forest Credits (UFC) adapted to the Brazilian reality has great potential to benefit the country in the carbon market and contribute to achieving its Greenhouse Gas (GHG) emission reduction goals.

Keywords: carbon neutrality, metalworking industry, carbon credits, urban forestry credits

Procedia PDF Downloads 55

Authors: Asavasereerat K., Teacharsripaitoon T., Tungyingyong P., Charupongrat S., Noppiboon S. Hochareon L., Kitsuban P.

Abstract:

Third generation of vaccines is based on gene therapy where DNA is introduced into patients. The antigenic or therapeutic proteins encoded from transgenes DNA triggers an immune-response to counteract various diseases. Moreover, DNA vaccine offers the customization of its ability on protection and treatment with high stability. The production of DNA vaccines become of interest. According to USFDA guidance for industry, the recommended limits for impurities from host cell are lower than 1%, and the active conformation homogeneity supercoiled DNA, is more than 80%. Thus, the purification strategy using two-steps chromatography has been established and verified for its robustness. Herein, pVax1/lacZ, a pre-approved USFDA DNA vaccine backbone, was used and transformed into E. coli strain DH5α. Three purification process parameters including sample-loading flow rate, the salt concentration in washing and eluting buffer, were studied and the experiment was designed using response surface method with central composite face-centered (CCF) as a model. The designed range of selected parameters was 10% variation from the optimized set point as a safety factor. The purity in the percentage of supercoiled conformation obtained from each chromatography step, AIEX and HIC, were analyzed by HPLC. The response data were used to establish regression model and statistically analyzed followed by Monte Carlo simulation using SAS JMP. The results on the purity of the product obtained from AIEX and HIC are between 89.4 to 92.5% and 88.3 to 100.0%, respectively. Monte Carlo simulation showed that the pVAX1/lacZ purification process is robust with confidence intervals of 0.90 in range of 90.18-91.00% and 95.88-100.00%, for AIEX and HIC respectively.

Keywords: AIEX, DNA vaccine, HIC, puification, response surface method, robustness

Procedia PDF Downloads 187

Authors: Muhammad Tahir

Abstract:

Purpose The purpose of the study is to find anchoring bias behavior in mutual fund return with its parent firm performance in Pakistan. Research Methodology The paper used monthly returns of equity funds whose parent firm exist from 2011 to 2021, along with parent firm return. Proximity to 52-week highest return calculated by dividing fund return by parent firm 52-week highest return. Control variables are also taken and used pannel regression model to estimate our results. For robust results, we also used feasible generalize least square (FGLS) model. Findings The results showed that there exist anchoring biased in mutual fund return with its parent firm performance. The FGLS results reaffirms the same results as obtained from panner regression results. Proximity to 52-week highest Xc is significant in both models. Research Implication Since most of mutual funds has a parent firm, anchoring behavior biased found in mutual fund with its parent firm performance. Practical Implication Mutual fund investors in Pakistan invest in equity funds in which behavioral bias exist, although there might be better opportunity in market. Originality/Value Addition Our research is a pioneer study to investigate anchoring bias in mutual fund return with its parent firm performance. Research limitations Our sample is limited to only 23 equity funds, which has a parent firm and data was available from 2011 to 2021.

Keywords: mutual fund, anchoring bias, 52-week high return, proximity to 52-week high, parent firm performance, pannel regression, FGLS

Procedia PDF Downloads 97

Authors: Azhar Ulhaq, Zubair Yameen, Almas Anjum

Abstract:

Frequency behaviour of self-excited induction generator (SEIG) wind turbines during control mode transition from grid connected to islanded mode is studied in detail. A robust control scheme for frequency regulation based on combined action of STATCOM, energy storage system (ESS) and pitch angle control for wind powered microgrid (MG) is proposed. Suggested STATCOM controller comprises a 3-phase voltage source converter (VSC) that contains insulated gate bipolar transistors (IGBTs) based pulse width modulation (PWM) inverters along with a capacitor bank. Energy storage system control consists of current controlled voltage source converter and battery bank. Both of them acting simultaneously after detection of island compensates for reactive and active power demands, thus regulating frequency at point of common coupling (PCC) and also improves load stability. STATCOM integrates at point of common coupling and ESS is connected to microgrids main bus. Results reveal that proposed control not only stabilizes frequency during transition duration but also minimizes sudden frequency imbalance caused by load variation or wind intermittencies in islanded operation. System is investigated with and without suggested control scheme. The efficacy of proposed strategy has been verified by simulation in MATLAB/Simulink.

Keywords: energy storage system, island, wind, STATCOM, self-excited induction generator, SEIG, transient

Procedia PDF Downloads 127

Authors: Jixiang Lei, Alexander Fuchs, Franz Pernkopf, Katrin Ellermann

Abstract:

Within the Space@Sea project, funded by the Horizon 2020 program, an island consisting of multiple platforms was designed. The platforms are connected by ropes and fenders. The connection is critical with respect to the safety of the whole system. Therefore, fault detection systems are investigated, which could detect early warning signs for a possible failure in the connection elements. Previously, a model-based method called Extended Kalman Filter was developed to detect the reduction of rope stiffness. This method detected several types of faults reliably, but some types of faults were much more difficult to detect. Furthermore, the model-based method is sensitive to environmental noise. When the wave height is low, a long time is needed to detect a fault and the accuracy is not always satisfactory. In this sense, it is necessary to develop a more accurate and robust technique that can detect all rope faults under a wide range of operational conditions. Inspired by this work on the Space at Sea design, we introduce a fault diagnosis method based on deep neural networks. Our method cannot only detect rope degradation by using the acceleration data from each platform but also estimate the contributions of the specific acceleration sensors using methods from explainable AI. In order to adapt to different operational conditions, the domain adaptation technique DANN is applied. The proposed model can accurately estimate rope degradation under a wide range of environmental conditions and help users understand the relationship between the output and the contributions of each acceleration sensor.

Keywords: fault diagnosis, deep learning, domain adaptation, explainable AI

Procedia PDF Downloads 155

Authors: Brian Moore, Stuart Woodcock, Dean Dudley

Abstract:

Mental health problems have significant social and economic consequences; however, many individuals do not seek traditional assistance for mental health difficulties. Martial arts training may provide an inexpensive alternative to traditional psychological therapy. While limited research has suggested martial arts training may be an efficacious intervention, the validity and reliability of this are questionable given the small number of relevant studies and other methodological problems. The study examined the effects of 10-week martial arts-based psycho-social intervention which was evaluated using a randomized controlled trial. The intervention was delivered to 283 secondary school students, aged between 12-14 years, who were recruited from government and catholic secondary schools in New South Wales, Australia. The intervention was delivered in a group format onsite at participating schools and had an intervention dose of 10 x 50-60 minute sessions, once per week for 10 weeks. Data were collected at baseline, post-intervention, and 12-week follow-up. Results found a consistent pattern for strength based wellbeing outcomes. All primary and secondary measures relating to resilience and self-efficacy improved for the intervention group and declined for the control group. As these findings were derived from a robust design and rigorous evaluation, they provide valid and reliable evidence that martial arts-based psycho-social interventions can be considered as an efficacious method of improving strength and wellbeing outcomes.

Keywords: martial arts, mental health, resilience, self-efficacy

Procedia PDF Downloads 136

Authors: Amina Farooq, Nauman Zafar Butt

Abstract:

This paper is about methods and tools for counting particles of interest, such as cells. A microfluidic system with interconnected electronics on a flexible substrate, inlet-outlet ports and interface schemes, sensitive and selective detection of cells specificity, and processing of cell counting at polymer interfaces in a microscale biosensor for use in the detection of target biological and non-biological cells. The development of fluidic channels, planar fluidic contact ports, integrated metal electrodes on a flexible substrate for impedance measurements, and a surface modification plasma treatment as an intermediate bonding layer are all part of the fabrication process. Magnetron DC sputtering is used to deposit a double metal layer (Ti/Pt) over the polypropylene film. Using a photoresist layer, specified and etched zones are established. Small fluid volumes, a reduced detection region, and electrical impedance measurements over a range of frequencies for cell counts improve detection sensitivity and specificity. The procedure involves continuous flow of fluid samples that contain particles of interest through the microfluidic channels, counting all types of particles in a portion of the sample using the electrical differential counter to generate a bipolar pulse for each passing cell—calculating the total number of particles of interest originally in the fluid sample by using MATLAB program and signal processing. It's indeed potential to develop a robust and economical kit for cell counting in whole-blood samples using these methods and similar devices.

Keywords: impedance, biochip, cell counting, microfluidics

Procedia PDF Downloads 140

Authors: Xuan Zheng

Abstract:

China is home to one of the world’s largest Deaf and Hard of Hearing (DHH) populations. In the 1980s, the concept of inclusive education was introduced, giving rise to a unique “learning in regular class (随班就读)” model tailored to local contexts. China’s inclusive education for DHH students is diversifying with innovative models like special education classes at regular schools, regular classes at regular schools, resource classrooms, satellite classes, and bilingual-bimodal projects. The scope extends to preschool and higher education programs. However, the inclusive development of DHH students faces challenges. The prevailing pathological viewpoint on disabilities persists, emphasizing the necessity for favorable auditory and speech rehabilitation outcomes before DHH students can integrate into regular classes. In addition, inadequate support systems in inclusive schools result in poor academic performance and increased psychological disorders among the group, prompting a notable return to special education schools. Looking ahead, China’s inclusive education for DHH students needs a substantial shift from “learning in regular class” to “sharing equal regular education.” Particular attention should be devoted to the effective integration of DHH students who employ sign language into mainstream educational settings. It is crucial to strengthen regulatory frameworks and institutional safeguards, advance the professional development of educators specializing in inclusive education for DHH students, and consistently enhance resources tailored to this demographic. Furthermore, the establishment of a robust, multidimensional, and collaborative support network, engaging both families and educational institutions, is also a pivotal facet.

Keywords: deaf, hard of hearing, inclusive education, China

Procedia PDF Downloads 25

Authors: Hsiao-Chuan Huang, King-Lung Kuo, Mei-Hsin Lo, Hsiao-Yun Chou, Yusen Lin

Abstract:

The most robust and economical method for laboratory diagnosis of TB is to identify mycobacterial bacilli (AFB) under acid-fast staining despite its disadvantages of low sensitivity and labor-intensive. Though digital pathology becomes popular in medicine, an automated microscopic system for microbiology is still not available. A new AI-assisted automated microscopic system, consisting of a microscopic scanner and recognition program powered by big data and deep learning, may significantly increase the sensitivity of TB smear microscopy. Thus, the objective is to evaluate such an automatic system for the identification of AFB. A total of 5,930 smears was enrolled for this study. An intelligent microscope system (TB-Scan, Wellgen Medical, Taiwan) was used for microscopic image scanning and AFB detection. 272 AFB smears were used for transfer learning to increase the accuracy. Referee medical technicians were used as Gold Standard for result discrepancy. Results showed that, under a total of 1726 AFB smears, the automated system's accuracy, sensitivity and specificity were 95.6% (1,650/1,726), 87.7% (57/65), and 95.9% (1,593/1,661), respectively. Compared to culture, the sensitivity for human technicians was only 33.8% (38/142); however, the automated system can achieve 74.6% (106/142), which is significantly higher than human technicians, and this is the first of such an automated microscope system for TB smear testing in a controlled trial. This automated system could achieve higher TB smear sensitivity and laboratory efficiency and may complement molecular methods (eg. GeneXpert) to reduce the total cost for TB control. Furthermore, such an automated system is capable of remote access by the internet and can be deployed in the area with limited medical resources.

Keywords: TB smears, automated microscope, artificial intelligence, medical imaging

Procedia PDF Downloads 196

Authors: Alvite Singh Ningthoujam

Abstract:

The most recent terror phenomenon, which is also known as the Islamic State of Iraq and Syria (ISIS), or Islamic State (IS), has its influence felt in South Asia. This dreaded Sunni militant group, today, has become a concern in India as well. Already affected by various terror activities in the country, the influence of the IS on the radicalised Muslim youths in India has been watched closely by the security agencies. There had already been a few IS-related incidents in India due to which this issue has emerged as a threat or challenge to India’s internal security. The rapid radicalisation of youths in a few states where there are sizeable Muslim populations has gone, to some extent, in favour of the IS, particularly in the terror outfit’s recruitment process. What has added to the worry of the Indian security agencies is the announcement of the Al-Qaeda leader, Ayman al-Zawahari, of the creation of the Al-Qaeda in the Indian Subcontinent. In fact, this is a worrisome factor as both the militant groups, that is, al-Qaeda and ISIS, have a similar objective to target India and to turn this South Asian country as one of the recruiting grounds for extremists. There is also a possibility that an Indian Mujahedeen (IM) man was believed to be instrumental in recruiting for the ISIS poor Muslims in a few Indian states. If this nexus between ISIS and India’s home-grown terror groups manages to establish a robust link, then the headache of combating such amalgamated force will be a hard task for Indian security agencies. In the wake of the above developments, this paper would seek to analyse the developing trend in India in regard to IS. It would also bring out the reasons as to why further penetration of the IS influence on India would be a grave concern in the internal security of the country. The last section of the paper would highlight the steps that have been taken by the Indian government to tackle this menace effectively.

Keywords: India, Islamic State, Muslim, Security

Procedia PDF Downloads 350

Authors: Asmamaw Yehun, Tsegaye Kassa, Addisu Hunegnaw, Martin Vermeer

Abstract:

There are various models to estimate the neutral atmospheric parameter values, such as in-suite and reanalysis datasets from numerical models. Accurate estimated values of the atmospheric parameters are useful for weather forecasting and, climate modeling and monitoring of climate change. Recently, Global Navigation Satellite System (GNSS) measurements have been applied for atmospheric sounding due to its robust data quality and wide horizontal and vertical coverage. The Global Positioning System (GPS) solutions that includes tropospheric parameters constitute a reliable set of data to be assimilated into climate models. The objective of this paper is, to estimate the neutral atmospheric parameters such as Wet Zenith Delay (WZD), Precipitable Water Vapour (PWV) and Total Zenith Delay (TZD) using six selected GPS stations in the equatorial regions, more precisely, the Ethiopian GPS stations from 2012 to 2015 observational data. Based on historic estimated GPS-derived values of PWV, we forecasted the PWV from 2015 to 2030. During data processing and analysis, we applied GAMIT-GLOBK software packages to estimate the atmospheric parameters. In the result, we found that the annual averaged minimum values of PWV are 9.72 mm for IISC and maximum 50.37 mm for BJCO stations. The annual averaged minimum values of WZD are 6 cm for IISC and maximum 31 cm for BDMT stations. In the long series of observations (from 2012 to 2015), we also found that there is a trend and cyclic patterns of WZD, PWV and TZD for all stations.

Keywords: atmosphere, GNSS, neutral atmosphere, precipitable water vapour

Procedia PDF Downloads 36